Hybrid card sorting: Blend open and closed methods for deeper IA insights
Team Askable
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February 11, 2026
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Hybrid card sorting gives teams the best of both worlds by combining the freedom of open card sorting with the structure of closed card sorting, creating a richer, more nuanced understanding of how users interpret and organize information.
Where open card sorting uncovers how users naturally group content and how they label categories, closed card sorting validates whether your proposed structure makes sense, hybrid card sorting sits right in the middle. Participants are presented with predefined categories but also given the option to create new ones. This approach reveals not only how well your existing labels work, but also where your structure falls short. If users repeatedly add new categories or place items outside your intended groups, it signals that your information architecture needs refinement. Hybrid card sorting becomes a diagnostic tool that identifies both alignment and gaps in user understanding.
This method is especially valuable when teams already have a draft IA but want to test its flexibility and discover additional nuance. Hybrid card sorting shows where categories overlap, where labels confuse users, and where mental models diverge across audiences. It also surfaces unexpected groupings that open card sorts often reveal, while still testing whether your primary IA framework holds. The combination of guided structure and open exploration gives teams deeper insight into how users think about content, how they interpret terminology, and how confidently they can place items in existing groups.
Hybrid card sorting scales well, producing both qualitative and quantitative insights. By observing which items participants confidently place into predefined categories and which require new groupings, teams can quantify clarity, measure friction, and identify areas for improvement. Adding behavioural observation, such as watching users hesitate, debate, or revise groupings, enriches the data further. With hybrid sorts, teams gain a multidimensional understanding of user expectations and can refine their IA with precision.
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Let's chatProduct teams use hybrid card sorting to validate and evolve the way features are structured within a product. It helps teams understand whether users see features as part of the same workflow or categorize them differently based on goals or mental models. If participants confidently use existing categories, the structure is likely on track. If they add new ones, product teams gain insight into missing concepts or more intuitive groupings. Hybrid sorts also help reduce onboarding friction by shaping product menus and dashboards around the categories users instinctively rely on. For feature heavy products, hybrid sorting provides clarity early in the decision making process.
Research teams rely on hybrid card sorting to explore both known structures and emerging mental models simultaneously. Because users can place cards in predefined categories or create new ones, researchers can measure alignment while uncovering patterns that might otherwise remain hidden. This method shows where language breaks down, where users struggle with conceptual differences, and how mental models evolve across demographics. Hybrid card sorting produces clean, structured data that researchers can compare at scale, but it also includes qualitative nuance that strengthens final recommendations. It is a powerful tool for building evidence based IA strategies.
Design teams use hybrid card sorting to evaluate whether their proposed navigation systems feel intuitive and to identify opportunities for improvement. The ability for participants to create new categories reveals whether labels are missing, unclear, or too broad. Watching participants reorganize content provides insights into how they think about tasks, how they expect information to be grouped, and what language resonates. Hybrid sorts are especially useful when moving from legacy navigation to a new structure because they validate current assumptions while capturing the exploratory thinking needed for innovation. For designers focused on findability and clarity, hybrid card sorting provides essential guidance.
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Contact salesAskable Card Sorting makes hybrid studies simple, scalable, and insight rich. The platform supports open, closed, hybrid, and ranked card sorts, giving teams complete flexibility across every stage of IA development. With a mobile optimized interface, participants can complete sorts easily on any device, increasing engagement and reducing drop offs. Randomized card order eliminates position bias automatically, while stack ranking allows users to prioritize items within groups for even deeper insights.
Askable provides both behavioural context and structured analysis. Full session recordings with participant audio let you watch how users discuss categories, why they create new ones, and where they hesitate or reconsider placements. These real time moments reveal the reasoning behind both intuitive and unexpected groupings. On the quantitative side, Askable’s built in analysis automatically groups similar category names, organizes messy inputs, and generates agreement matrices that show which groupings are strong versus uncertain. There is no need to spend hours wrangling spreadsheets.
Exporting insights is fast and flexible. Teams can download presentation ready visuals, raw CSV files for deeper analysis, and share results confidently with stakeholders. Powered by Askable’s verified global participant pool across more than 5,300 cities and over 15 languages, plus a 97.8 percent show rate, you get reliable, high quality data every time. Whether you are creating a new IA, refining a complex navigation system, or validating evolving structures, Askable hybrid card sorting gives you deeper, more actionable insights.
What is hybrid card sorting?
Hybrid card sorting combines open and closed methods by allowing participants to sort cards into predefined categories or create new ones if necessary.
Why is hybrid card sorting useful?
It reveals how well your existing IA works while uncovering new mental models, gaps, and opportunities to refine labels and structure.
How do product, research, and design teams use hybrid sorts?
Product teams validate feature grouping, research teams explore mental models at scale, and design teams refine navigation structures based on real behaviour.
Does Askable support hybrid card sorting?
Yes. Askable offers open, closed, hybrid, and ranked sorts with built in analysis and session recordings.
What makes Askable Card Sorting unique?
Mobile optimized sorting, session recordings, automatic category grouping, agreement matrices, randomized card order, and access to global participants create a clear, powerful research workflow.
If you want to understand not just whether your categories work but why users group information the way they do, hybrid card sorting with Askable gives you everything you need. Blend structure with exploration, observe real behaviour, and refine your IA with confidence. Try Askable Card Sorting today and build navigation systems rooted in real user thinking.
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